[IPython-dev] Docker IPython

[Kyle Kelley]

I'm definitely on the pip for base image camp. conda can be installed after
as part of a separate image. We also don't need to manage multiple
environments. It is one container after all. Derivatives can have
components.


On Tue, Aug 5, 2014 at 12:36 PM, Matthias Bussonnier <
bussonniermatthias at gmail.com> wrote:

>
> Le 5 août 2014 à 18:11, Jon Wilson <jsw at fnal.gov> a écrit :
>
> > If any substantial fraction of your users will want
> > scipy/numpy/matplotlib, I would (almost, see below) recommend conda.
>
> Adrew’s IHaskell users will definitively not want the scipy stack, they
> want Haskell things.
>
>
> > Conda was, as I understand it, created because pip left too many
> > barriers in place against the use of scipy/numpy etc.  Specifically,
> > experience indicated that many people who might otherwise have casually
> > investigated scientific python tools did not do so because pip required
> > them to have a proper FORTRAN development environment set up, and they
> > did not wish to figure out how to do this.
> >
> > Conda distributes binaries rather than exclusively source, which is an
> > effective way around this sort of problem.
> >
> > OTOH, a pure-python package that is hosted on PyPI (and therefore
> > installable via pip) can (usually) be trivially made into a conda
> > package via `conda skeleton pypi <package-name>`.  So making pip-style
> > packages tends to get you conda packages for almost free.
>
> I suppose this « easy » way to make PyPi package from conda package explain
> why  continuum package are outdated by more that a year using pip :-)
>
> Even if conda seem great, I still feel sad that there is little effort to
> help fixing
> python packaging (no, replacing is not fixing), but I understand that
> starting
> from scratch might be easier. Installig SciPy was much more a pain even a
> few
> month ago than now.
>
> Keep also  in mind than miniconda will be smaller if you decide to use it.
>
> I would also reming you that with 3.0, the IPython notebook can start many
> kernels in different languages,
> so nothing prevent you from installing the notebook using pip, and having
> a conda kernel.
> (it is even possible with 2.x)
>
> So +1 for pip which should be enough, or even maybe Julia Taylor PPA if
> compatible.
> —
> M
>
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-- 
Kyle Kelley (@rgbkrk <https://twitter.com/rgbkrk>; http://lambdaops.com)
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